Autonomous mobile nodes such as unmanned airborne nodes (UANs) or unmanned aerial vehicles (UAVs) are often useful in various military and civilian applications. Maintaining constant and reliable communication between mobile entities, distributed or located across a large geographical area has been, however, a critical task for many commercial applications as well as military applications. For example, when teams of people are deployed in hostile or sensor deprived environments, maintaining radio contact with a command station or site would increase efficiency of coordinating the deployment and accomplishing mission objectives, yet maintaining communications should not interfere with the primary tasks of these entities.
Conventionally, most unmanned airborne nodes including unmanned aerial vehicles (UAVs), are operated remotely by a single operator. As such, forming a mobile communication network with multiple remotely controlled unmanned aerial vehicles can be prohibitively costly. Also, it is very inefficient because many operators are needed to remotely control the deployed unmanned airborne nodes, while coordinating with others to monitor the deployed communications network. Furthermore, there is no effective mechanism to deal with airborne node faults or failures in hardware or software when they are in flight. Such faults or failures may result an action or behavior becoming anomalous, meaning that it diverged from its normal or expected outcome.
Due to all of the above, there is a need for improved methods and systems for detecting anomalies and providing decision support to a human operator of one or unmanned airborne nodes, identifying possible causes of the detected anomalies, and recommending corrective measure.